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‫So let's talk about

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‫Customization At The Edge.

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‫So what does it mean?

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‫Well we know we deploy our functions

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‫and our applications in a specific region,

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‫but sometimes using, for example, CloudFront,

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‫we have the Edge locations are distributing our content.

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‫And sometimes the modern applications require

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‫to execute some form of logic at the Edge

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‫before reaching the application itself.

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‫So these are called Edge Functions,

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‫and this is a piece of code that you write

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‫and that you will attach to your CloudFront distributions.

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‫The idea is that you want to run these functions

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‫close to users in order to minimize latency in some cases.

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‫So CloudFront has two kinds of functions,

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‫you have the CloudFront Functions and Lambda@Edge.

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‫The idea will be to be able to understand

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‫when they are required and their differences,

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‫and will do this in this lecture.

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‫But using the Edge Functions,

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‫you don't have to manage any servers,

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‫these Edge Functions are deployed globally.

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‫And the use cases of them,

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‫for example, would be to customize the CDN content

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‫coming out of CloudFront.

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‫Also, you only pay for what you use,

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‫and it is fully serverless.

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‫So now let's have a deeper look

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‫into these things, the use cases.

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‫The first one is around website security and privacy,

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‫then we have dynamic web applications at the Edge,

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‫we can do search engine optimization, SEO,

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‫we can do intelligent routing across

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‫Origins and data center,

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‫Bot mitigation at the Edge,

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‫real-time image transformation at the Edge,

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‫A/B testing, user authentication and authorization,

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‫user prioritization, user tracking and analytics, and so on.

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‫So this is a lot of different customizations

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‫we can have using CloudFront Functions and Lambda@Edge.

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‫So now let's discuss what CloudFront Functions

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‫are used for and how they work.

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‫So this is what a typical request

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‫into CloudFront looks like.

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‫So the client will do a request into CloudFront,

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‫and this is called a viewer request,

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‫because the client views it.

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‫Then CloudFront will do an origin request

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‫into your origin server,

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‫the server will reply to CloudFront,

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‫so we have an origin response,

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‫and finally CloudFront sends that response to the client,

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‫so we have a viewer response.

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‫Now CloudFront Functions are lightweight functions

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‫written in JavaScript,

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‫and they modified the viewer request and response.

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‫They're used for high-scale,

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‫latency-sensitive CDN customizations,

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‫which gives you sub-millisecond startup times,

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‫and a scale of millions of requests per second.

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‫As I said, they're used to change viewer request

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‫and responses only,

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‫so the view request is after CloudFront

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‫receives a request from a viewer, we can modify this,

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‫or the viewer response is to

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‫before CloudFront forwards the response back to the viewer.

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‫It's a native feature of CloudFront,

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‫and the entire code is managed

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‫from within CloudFront directly.

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‫Remember, CloudFront Functions high performance,

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‫high scale only for the viewer request and response.

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‫Now Lambda@Edge is a bit more,

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‫so you can modify all of them.

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‫So these are functions returned in NodeJS or Python,

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‫and you scale to 1000s of requests per second,

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‫and it's used to change CloudFront request

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‫and response, multiple ones, so all of them actually,

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‫the viewer request and the origin request,

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‫which is before CloudFront forwards a request to the origin.

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‫You also have the origin response,

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‫which is after CloudFront receives the response

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‫from the origin, and the viewer response,

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‫which is before CloudFront forwards

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‫the response back to the viewer.

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‫You author your function in one region,

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‫which is us-east-1, which is the same region

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‫where you manage your CloudFront distributions,

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‫and then CloudFront is going to replicate this function

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‫to all of its locations.

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‫So we have a table here to differentiate

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‫between CloudFront Functions and Lambda@Edge.

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‫So one notable difference is the runtime support,

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‫of course JavaScript only for CloudFront Functions,

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‫and then NodeJS and Python for Lambda@Edge.

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‫The scale is really, really high scale

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‫for CloudFront Functions, we're talking about

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‫millions of requests per second,

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‫versus thousands for Lambda@Edge.

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‫Now where the trigger is happening is a big difference.

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‫So Lambda@Edge has impact on both

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‫the viewer request and the origin,

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‫whereas the CloudFront Functions is only on the viewer.

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‫And very important, the max execution time

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‫is less than one millisecond for CloudFront Functions,

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‫so they're very, very quick and simple functions.

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‫Whereas for Lambda@Edge you can get

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‫up to 5 to 10 seconds,

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‫so you can perform a lot of logic in these functions.

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‫The rest, you can have a look, okay?

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‫Now in terms of use cases,

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‫CloudFront Functions is going to be for

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‫cache key normalization,

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‫so to transform, for example the request attributes

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‫to create an optimal cache key.

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‫Header manipulation to insert, modify, or delete

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‫HTTP headers in the request or response,

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‫or to do URL rewrites or redirects,

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‫or to request of an authorization

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‫to create and validate JWT tokens to allow or deny request.

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‫So all these things can be executed

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‫in less than one millisecond,

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‫whereas Lambda@Edge has a longer execution time,

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‫it could be up to 10 seconds, for example.

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‫You have adjustable CPU and memory,

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‫so you can load a lot of libraries,

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‫and your code can depend therefore,

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‫on third party libraries, such as the SDK

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‫if you wanted to access other AWS services.

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‫You also have network access to external services

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‫for processing the data,

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‫so you can really perform some big integrations.

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‫And Lambd@Edge gives you file system access,

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‫or access to the body itself of the HTTP request,

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‫so you can do some more customizations.

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‫So hopefully that helps you.

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‫I hope you liked this lecture,

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‫and I will see you in the next lecture.